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Measuring the efficiency of administrative divisions in combating the COVID‐19 pandemic in Taiwan: an empirical study.
- Source :
- International Transactions in Operational Research; Mar2025, Vol. 32 Issue 2, p1064-1087, 24p
- Publication Year :
- 2025
-
Abstract
- The coronavirus disease 2019 (COVID‐19) pandemic continues to have a substantial impact on the economies and livelihoods of all countries. Central and local government administrators are facing a critical issue of resource utilization efficiency due to their limited resources. This paper employs data envelopment analysis (DEA) and the concept of an assurance region (AR) to assess the relative efficiency of administrative divisions in Taiwan, whose effectiveness has been praised by other countries' administrators and citizens, regarding COVID‐19 pandemic prevention and control. The input factors used were the cumulative number of deaths (an undesirable factor) and expenditures, and the output factors were the average number of unconfirmed citizens aged 65 and older, the average number of unconfirmed citizens aged 0–64, and the cumulative number of vaccinations. Notably, because there are many COVID‐19 variants with different characteristics, reaching a consensus AR among experts is difficult. Thus, different ARs were compared, and the most representative AR was identified for subsequent analysis. The main findings show that only Kaohsiung City was efficient, and Taipei City was the third worst due to inefficient operations. In addition, the administrative divisions were classified into four groups using cluster analysis based on the decomposition of aggregate efficiency to the contributions of the three outputs. The findings presented in this paper serve as a reference for both local government administrators and citizens, offering insights into relative efficiency and improvement directions. Moreover, they also provide guidance for resource allocation, future strategy adjustment, and development for central government administrators and citizens worldwide. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09696016
- Volume :
- 32
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- International Transactions in Operational Research
- Publication Type :
- Academic Journal
- Accession number :
- 180069193
- Full Text :
- https://doi.org/10.1111/itor.13341